Publications by authors named "Tatsuhiko Iwase"

A ready-made dry medium method for Staphylococcus aureus count, the Medi·Ca SA method incubated at 35 or 37°C, was compared with the Baird-Parker method (AOAC Official MethodSM 975.55) for 11 food matrices: raw beef, raw ground beef, raw lamb, cooked ham, raw salmon, frozen prawn, fresh chilled pasta, pasteurized milk, natural cheese, cream puff, and potato salad. The mean difference between the two methods at each contamination level for each matrix was <0.

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A ready-made dry medium method for Escherichia coli and coliform count, the Medi·Ca EC method, was compared with the most probable number (MPN) method using Brilliant Green Lactose Bile broth and E. coli broth (AOAC INTERNATIONAL Official MethodSM 966.24) for seven food matrixes: raw beef, raw pork, raw frozen pork, raw lamb, raw salmon, frankfurter sausage, and cooked ham.

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Although mitogen-activated protein kinase kinase (MEK) is a key signaling molecule and a negative regulator of insulin action, it is still uncertain whether MEK can be a therapeutic target for amelioration of insulin resistance (IR) in type 2 diabetes (T2D) in vivo. To clarify whether MEK inhibition improves T2D, we examined the effect of continuous MEK inhibition with two structurally different MEK inhibitors, RO5126766 and RO4987655, in mouse models of T2D. RO5126766 and RO4987655 were administered via dietary admixture.

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A ready-made dry medium method for coliform count, the Medi·Ca CC method, was compared to the Violet Red Bile Agar method (Bacteriological Analytical Manual, Chapter 4, Enumeration of Escherichia coli and the Coliform Bacteria, Section G) for nine raw foods from four food categories: raw ground pork, raw lamb, raw ground chicken, raw tuna fillet, raw salmon fillet, raw shrimp, fresh peeled banana, fresh cut pineapple, and fresh cut apple. The 95% confidence interval for the mean difference between the two methods at each contamination level for seven matrixes from all four categories fell within the range of -0.50 to 0.

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An automated method for measurement of arteriolar-to-venular diameter ratio (AVR) is presented. The method includes optic disc segmentation for the determination of the AVR measurement zone, retinal vessel segmentation, vessel classification into arteries and veins, selection of major vessel pairs, and measurement of AVRs. The sensitivity for the major vessels in the measurement zone was 87%, while 93% of them were classified correctly into arteries or veins.

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